DocumentCode
1640338
Title
Fault diagnosis for dynamical systems using soft computing
Author
Yakuwa, Fnminori ; Satoh, Shingo ; Shaikh, Muhammad Shafique ; Dote, Yasuhiio
Author_Institution
Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
261
Lastpage
266
Abstract
Fault diagnosis schemes for small-scale systems using novel fuzzy-neural networks with general parameter learning and time delay neural networks with linear regressions, are described. Then a new fault diagnosis approach for large-scale systems employing the fuzzy-neural network and immune network is introduced. Results from real world applications are presented
Keywords
fault diagnosis; fuzzy neural nets; large-scale systems; learning (artificial intelligence); statistical analysis; fault detection; fault diagnosis; fuzzy-neural networks; general parameter learning; immune network; large-scale systems; linear regressions; time delay neural networks; Artificial intelligence; Automobiles; Delay effects; Fault detection; Fault diagnosis; Finite impulse response filter; Gears; Linear regression; Neural networks; Radial basis function networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7280-8
Type
conf
DOI
10.1109/FUZZ.2002.1004997
Filename
1004997
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